The near-nature forestry construction is an important direction for landscape development in future.As spe-cies with potential landscape value in a large number but short of introduction practice,it has important significance to carry out introduction regionalization in only wild distribution data condition.The principle of MaxEnt ecological model is predicting potential distribution rang of species based on the wild species distribution data together with wild species distribution and climate adaptation on the premise,which is consistent with the need for identifying the intro-duction regionalization of potential landscape plants in near-nature forestry.In the study,Hedychium coccineum was used to be an example to evaluate the valid of introduction regionalization conducted by MaxEnt modeling frameworkaccording to the theoretical method together with introduction practice.Temperature ,rainfall and altitude environ-mental factors were selected to be analyzed on the basis of collection for geography distribution data.And 75% data were used to construct model while the remaining were used to evaluate the valid of model by drawing receiver oper-ating characteristic (ROC)plot.At last,suitable categories were determined by comparing the cultivated data with prediction map.The results showed that the area under the curve (AUC)was 0.991 diagnosed as excellent,which in-dicated that the model was highly reliable.Meanwhile,all the data were used to make a predicition map in MaxEnt. Further,categories were divided by comparing the location of introduction data with the map.The results indicated that H .coccineum could be cultivated successfully in the area where the above 0.01 when the suitability degrees be-tween 0 and 1 were divided into eleven categories.In all,if the wild plant to be introduced in near-nature forestry,the highly reliable introduction regionization map could be made in MaxEnt.%近自然林的营建是园林景观的一个重要发展方向.由于待引种的野生植物种类繁多且缺少引种栽培实践,如何在仅有野生分布数据的条件下进行植物的引种区划具有重要意义.MaxEnt(Maximum entropy method)的原理是基于物种分布与气候相适应,以物种野生分布数据为基础,寻找物种的潜在分布区,与近自然林条件下野生植物引种区划的需要一致.该文以红姜花为例采用理论和实践检验相结合的方法,对 Max-Ent 模型的有效性进行评价.在收集红姜花的野生地理分布数据基础上,选择温度、降雨、海拔为环境因子,以75％的数据进行建模,25％的分布数据作为检验作 ROC(Receiver operating characteristic)曲线对模型的有效性进行评价.结果表明：ROC 曲线下面积 AUC 值为0．991,评价结果优秀,表明预测模型可靠性高；进一步以全部分布数据在 MaxEnt 中制作区划图,将引种栽培数据的分布位置与区划预测图进行比对,划分适生性等级；在适生性被划分为0~1的11级时,区划图中大于0．01的区域内红姜花即可成功引种.结果证明对于缺少引种栽培实践、拟采用近自然林模式栽培的野生植物,可采用 MaxEnt 生态学模型制作引种区划图.
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